octave-se-resnet-50-0.125¶

Use Case and High-Level Description¶

The octave-se-resnet-50-0.125 model is a modification of se-resnet-50 from this paper with octave convolutions from Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution with alpha=0.125. As origin, it’s designed to perform image classification. For details about family of octave convolution models, check out the repository.

The model input is a blob that consists of a single image of 1, 3, 224, 224 in RGB order. The RGB mean values need to be subtracted as follows: [124, 117, 104] before passing the image blob into the network. In addition, values must be divided by 0.0167.

The model output for octave-se-resnet-50-0.125 is the typical object classifier output for the 1000 different classifications matching those in the ImageNet database.

Specification¶

Metric	Value
Type	Classification
GFLOPs	7.246
MParams	28.082
Source framework	MXNet*

Accuracy¶

Metric	Value
Top 1	78.706%
Top 5	94.09%

Input¶

Original model¶

Image, name - data, shape - 1, 3, 224, 224, format is B, C, H, W, where:

B - batch size
C - channel
H - height
W - width

Channel order is RGB. Mean values - [124, 117, 104], scale value - 59.880239521

Converted model¶

Image, name - data, shape - 1, 3, 224, 224, format is B, C, H, W, where:

B - batch size
C - channel
H - height
W - width

Channel order is BGR

Output¶

Original model¶

Object classifier according to ImageNet classes, name - prob, shape - 1, 1000, output data format is B, C, where:

B - batch size
C - predicted probabilities for each class in [0, 1] range

Converted model¶

Object classifier according to ImageNet classes, name - prob, shape - 1, 1000, output data format is B, C, where:

B - batch size
C - predicted probabilities for each class in [0, 1] range

Download a Model and Convert it into Inference Engine Format¶

You can download models and if necessary convert them into Inference Engine format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

python3 <omz_dir>/tools/downloader/downloader.py --name <model_name>

An example of using the Model Converter:

python3 <omz_dir>/tools/downloader/converter.py --name <model_name>

Legal Information¶

The original model is distributed under the following license :

MIT License

Copyright (c) Facebook, Inc. and its affiliates.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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